d2c-marketing

d2c-marketing is a skill for Claude Code from arnabbagxd/Brand-building-skills. It costs 126 tokens per session (2,228 once invoked), scanned A, original, MIT.

A marketing workflow for direct-to-consumer brands, meaning companies that sell to customers themselves instead of through retailers, distributors, or marketplaces.

In plain words
What is it for?
It helps plan customer acquisition, first purchases, retention, email and text-message flows, social proof, subscriptions, and repeat buying.
Why use it?
It addresses the challenge of gaining customers while also keeping the relationship, purchase data, and repeat sales within the brand's own channels.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the brand-building-skills plugin — 29 skills shipped together

Good fit It helps plan customer acquisition, first purchases, retention, email and text-message flows, social proof, subscriptions, and repeat buying.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/arnabbagxd/brand-building-skills/d2c-marketing
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add arnabbagxd/Brand-building-skills --skill d2c-marketing
Clone the repo
git clone --depth 1 https://github.com/arnabbagxd/Brand-building-skills

Made for: Claude Code.

Or install brand-building-skills, the plugin that ships this one along with the rest of its 29 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for d2c-marketing

README.md
[![agentmods](https://agentmods.dev/badge/skills/arnabbagxd/brand-building-skills/d2c-marketing/github.svg)](https://agentmods.dev/skills/arnabbagxd/brand-building-skills/d2c-marketing)
Your own site
<a href="https://agentmods.dev/skills/arnabbagxd/brand-building-skills/d2c-marketing"><img src="https://agentmods.dev/badge/skills/arnabbagxd/brand-building-skills/d2c-marketing/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for d2c-marketing

Your own site · 80×15
<a href="https://agentmods.dev/skills/arnabbagxd/brand-building-skills/d2c-marketing"><img src="https://agentmods.dev/badge/skills/arnabbagxd/brand-building-skills/d2c-marketing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 126 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,228 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 12 Jun 2026
  • Snyk pass 12 Jun 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00126 $0.02228
Opus 5 $0.00063 $0.01114
Sonnet 5 $0.00025 $0.00446
Haiku 4.5 $0.00013 $0.00223

Measured 13d ago against content hash b77fb6e1ee50, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

d2c-marketing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/d2c-marketing/SKILL.md · 230 lines

How it starts

The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.

D2C Marketing

You are a DTC marketing strategist. Your job is to build a full direct-to-consumer marketing system — from first touch to loyal repeat buyer — without relying on retail, distributors, or marketplaces.

Before You Start

Check if .agents/brand-context.md exists. Read it first. DTC marketing must be built on top of clear brand positioning and audience definition.


What Makes DTC Different

DTC brands own the entire customer relationship — no retailer buffer, no marketplace algorithm, no distributor margin. This means:

  • Higher margins but higher CAC — you pay for every customer yourself
  • Full data ownership — you see every click, purchase, and return
  • Direct relationship — email, SMS, and retargeting are your moat
  • Brand is the differentiator — DTC customers choose you specifically, not just the category

The DTC marketing flywheel: Acquisition → First Purchase → Retention → Advocacy → Lower CAC


Information to Gather

  1. Product — what is it? Price point? Consumable (repeat) or one-time?
  2. Current stage — pre-launch, early (0–1K customers), growth (1K–50K), scale (50K+)?
  3. Current channels — what acquisition channels are active?
  4. Unit economics — what's the current CAC, AOV, LTV? (if known)
  5. Retention data — repeat purchase rate, average orders per customer per year?
  6. Hero product vs. range — one flagship product or a full catalog?

Output: DTC Marketing System


01 — DTC UNIT ECONOMICS BASELINE

Before any marketing, establish the math:

Key metrics to define:

  • AOV (Average Order Value) — current or target
  • Target CAC — maximum you can spend to acquire a customer profitably
  • LTV (Customer Lifetime Value) — AOV × purchases per year × average retention years
  • LTV:CAC ratio — target 3:1 minimum, 5:1 for healthy DTC
  • Contribution margin — revenue minus COGS and fulfillment (what's left to spend on marketing)
  • Payback period — how many months until CAC is recovered

Read the full file on GitHub · 230 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 13d ago First seen · 230 lines · 126 tokens per session scan A b77fb6e1ee50

Subscribe to this mod's changes

d2c-marketing is a skill published in the GitHub repository arnabbagxd/Brand-building-skills (637 stars, last pushed 3mo ago), licensed MIT. It adds 126 tokens to every session and 2,228 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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